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Limits of Predictability in Commuting Flows in the Absence of Data for Calibration

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A paper by graduate student Yingxiang Yang, Professor Marta Gonzalez and others in the July 11 issue of Scientific Reports explains how to calculate the number of short and long commuting trips when detailed trip data is not available. They found that cell phone records from Rwanda and other countries can provide this information on a population’s commuting patterns. Compared with empirical trip data from the United States, their model’s estimation accuracy is as good as other existing models that depend on data for calibration. Obtaining quality estimates of how many people frequently travel between two places is a key ingredient for transportation planning, facility distribution and modeling the spread of infectious diseases. Read the full paper: https://www.nature.com/srep/2014/140711/srep05662/full/srep05662.html